Evidence map›Paper›PMID 30095857›Full record

ArticleHuman mutation2018

Quantifying the potential of functional evidence to reclassify variants of uncertain significance in the categorical and Bayesian interpretation frameworks.

Sarah E Brnich, Edgar A Rivera-Muñoz, Jonathan S Berg

Abstract read
In one paragraph

Article in Human mutation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. An accurate cellular assay to determine pathogenicity of coding and noncoding variants in Lynch syndrome genes.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  15. A Novel Human SDHA-Knockout Cell Line Model for the Functional Analysis of Clinically Relevant SDHA Variants.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sarah E BrnichDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-3460-4905
Edgar A Rivera-MuñozDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0002-0610-4770
Jonathan S BergDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-2360-2664

Funding

The Clinical Genome Resource – Advancing genomic medicine through biocuration and expert assessment of genes and variants at scaleU24HG009650 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JONATHAN S BERG, Jessica Ezzell Hunter · 2021 to 2026
$30.0M
MEDICAL SCIENTIST TRAINING PROGRAMT32GM008719 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI DARVILLE, TONI, DESHMUKH, MOHANISH P · 1999 to 2023
$15.1M
The Clinical Genome Resource - Expert Curation and EHR IntegrationU41HG009650 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERG, JONATHAN S · 2017 to 2020
$13.3M
A Knowledge Base for Clinically Relevant Genes and VariantsU01HG007437 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERG, JONATHAN S, EVANS, JAMES PHILIP · 2013 to 2016
$9.0M
NRSA IN GENETICST32GM007092 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SEKELSKY, JEFF J. · 1985 to 2019
$5.9M
NHGRI NIH HHS U01 HG007437NHGRI NIH HHS U24 HG009650NHGRI NIH HHS U41 HG009650NIGMS NIH HHS T32 GM007092NIGMS NIH HHS T32 GM008719
6 · The paper itself

Abstract

Additional variant interpretation tools are required to effectively harness genomic sequencing for clinical applications. The American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP) published guidelines for clinical sequence variant interpretation, incorporating different types of data that lend varying levels of support towards a benign or pathogenic interpretation. Variants of uncertain significance (VUS) are those with either contradictory or insufficient evidence, and their uncertainty complicates patient counseling and management. Functional assays may provide a solution to evidence gaps relegating variants to the VUS category, but the impact of functional evidence in this framework has not been assessed. We employ an algorithmic analysis of the ACMG/AMP combining rules to assess how the availability of strong functional evidence could theoretically improve the ability to make a benign or pathogenic assertion. We follow this with analysis of actual evidence combinations met by variants through expert curations as part of the Clinical Genome Resource (ClinGen). We also examine the impact of functional evidence in a Bayesian adaptation of the ACMG/AMP framework. This lays the groundwork for an evidence-based prioritization of assay development and variant assessment by identifying genes and variants that may benefit the most from functional data.

Indexed as

Bayes TheoremComputational BiologyGenetic TestingGenetic VariationGenome, HumanGenomicsHigh-Throughput Nucleotide SequencingHumansMutationSequence Analysis, DNASocieties, MedicalSoftwareUnited StatesACMG/AMP guidelinesBayesianfunctional assayvariant interpretationVUS

Identifiers

PMID30095857
PMCPMC6548460

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.